Settlement Analysis On Soft Groud Of The Expressway

Since the reform and open to the outside world, the economic development of our country is increasing.Meanwhile, as an important part of the basic construction, highway also have developed rapidly. But many highway have to build on the soft soil foundation because the geography condition restriction. Soft soil properties is very special.If the treatment of soft soil is bad, in actual project will appear a lot of problems. For example:pavement become jagged, causing water, the bridge jumped, and even the whole road damage.Therefore, it is a hot and difficult point to build highways on soft soil foundation for many scholars in recent years. Because of soft soil properties complex and the parameters are difficult to be determined, the existing calculation and prediction models have theirs limitations. Highway requirements are demanding. The traditional forecasting method is often have a lot of errors for the soft soil foundation. How to improve the subsidence prediction method, based on the measured data accurately predict roadbed final settlement amount is our urgent problems at present.This paper introduces some presently used foundation treatment method. With SuiYueNa highway subsidence observation data as the foundation, analyzes several different foundation treatment method in different parts of the effect achieved by. Meanwhile proof according to specific geological conditions, plastic drainage board instead of CFG pile in the bridge's application is also very successful.This paper is focusing on the settlement deformation mechanism of soft soil foundation. This paper introduced some presently used settlement calculation method and subsidence prediction model and analyzes and summarizes the applicability of these methods. With SuiYueNa highway for engineering rely on, the paper analyzes four basic subsidence prediction method, and puts forward the research with four methods of variable combinatorial model. Through the comparison with the measured data, shows that this model can accurately predict foundation subsidence and avoid the single forecasting methods one-sidedness and limitations.